Should I include anything else for this correlation analysis?
Okay kind of a long post but I want to make sure I am doing this project right.
"Collect continuous quantitative data that is appropriate for regression and correlation analysis. include at least 30 (x,y) pairs of observations in your sample."
x= minutes you brush your teeth on a daily basis.
y= minutes you take a showers on a daily basis.
I'm pretty sure these are both continuous because I'm recording time which is never discrete.
Once I have my data I am to use descriptive statistics to completely describe the distribution (shape, center, spread) of my data and include an interpretation of these summaries.
For using descriptive statistics I have
Sample size, mean, median, mode, range, min, max, Q1, Q3, IQR, possible outliers, Skeweness in the distribution, distributions (unimodal, etc), varriance, std dev, and std error. I have all of these for each of my variables x and y.
For the correlation analysis I have
r-sq, r coefiicient, y-intercept, slope, (slopes p-value, t-statistic, std error, and degrees of freedom) and (y-intercepts p-value, t-statistic, std error, and degrees of freedom).
Question: Is there any other data I can use to further describe the distrubtion of either the variables by themselves or the correlation between the two?
Question: How can I evaluate the validity of my assumptions for the inference methods used in this case? (is it like make sure they are random and have 15 success and 15 failiures type of validity or would it be different with correlation analysis)
Question: How would I go about finding the confidence interval and use the hypothesis testing to examine the form and stregnth of the relationship between my two variables. I could figure out the confidence interval but not sure about the hypothesis testing. I understand hypothesis testing as well, the 5 steps and all just not how to do it for (x,y) variables.
I thank you ahead of time for at least reading my entire post.